This is toolbox makes it very easy to do wavelet coherence analysis:
The thumbnail image was generated by calling:
wt: continuous wavelet plot
xwt: cross wavelet plot
wtc: wavelet coherence plot
Aslak Grinsted (2020). Cross wavelet and wavelet coherence (https://github.com/grinsted/wavelet-coherence), GitHub. Retrieved .
How does this differ from:
Great toolbox. I thank Grinsted for helping me finished my thesis about paleo-drought in Maritime Continent!
I need to now how could I plot Partial and Multiple wavelet coherence? Please help me to plots.
Excuse me, I just want to inquire how to change 'period/scale' to frequency?
How to change period/scale?
I use Matlab r2018a and it comes with a function "wcoherence" that returns the magnitude-squared wavelet coherence between two equal length signals. Is the function "wtc" of this toolbox differ from that function? If yes, then how?
How to change the scale?
it used to work perfectly, but now I get the following error:
Error using wtc (line 116)
Automatic AR1 estimation failed. Specify it manually (use arcov or arburg).
Error in untitled (line 3)
How to bring the code back to life?
So far, an excellent tool. I have a question about the cache, I seem to get this error when running wtc:
"Warning: Unable to write to cache file:
> In wtcsignif at 156
In wtc at 163 "
Perhaps there's a problem with the permissions of the location where I've stored the toolbox? Any suggestions?
I get the following error while running wavelet coherence b/w EEG and center-of-mass velocity during a posture task (this can take negative values)
"Subscript indices must either be real positive integers or logicals.
Error in rednoise (line 55)
Error in wtcsignif (line 119)
Error in wtc (line 163)
On some investigation, I observed that this is generated because the Lag one covariane comes out to be greater than Lag 0 covariance in "ar1nv.m", because of which, the estimate of noise variance is a complex number instead of a real number (as g>1).
So, I was wondering if there is any way around it?
how to install it on Matlab R2016b
God bless you.
@student: yes you need to fill the data gaps. for example using interpolation ofr the mean value. If the gaps are much shorter than the shortest wavelength you are interested in then they wont have much effect on the output.
I have data every 10 minutes.
The software does not accept lack of data in some time (the software does not run with NaN).
I can replace the NaN by ZERO ?? Would you have any suggestions without having to share the data file?
Thanks in advance
useful for any discipline
Great job, thank you!